Unmanned aerial vehicles (UAV) have recently emerged as a valuable technological asset tailored for diverse assignments ranging from area or target surveillance and psychological operators to critical equipment pickup or delivery, while maintaining a low observability profile. In addition, they can operate in swarms, multiplying their efficiency under appropriate coordination schemes, which require precise communication and multiple sensor readings along with sophisticated algorithmic principles such as the Hamilton-Jacobi-Bellman equations. UAV capabilities are important in contemporary urban metroplexes where the smart deployment of small, light, and highly mobile parties acting and reacting rapidly in all three dimensions based on local intelligence is crucial. In these scenarios as well as in many more the location and the trajectory of a UAV is of utmost importance. Mining for latent patterns is one way to gain insight from them, which is largely facilitated by the advent of digital twinning. The efficient translation of geometric quantities such as location and velocity to computational ones is examined and related considerations are enumerated. Moreover, the conditions for deriving efficient and proper Julian code for digital twinning purposes are detailed.